X-ray crystallography is an important tool for analysing crystals and has a central role in technical fields such as mineralogy, metallurgy, biology, and pharmacology. Traditionally X-ray crystallography has been based on either single crystals or powders. Single crystal X-ray crystallography provide superior information compared to powder X-ray crystallography but require larger crystals. Thus, a significant amount of work has to be performed in e.g. pharmacology for growing mono grain crystallites of a size and quality required for X-ray crystallography analysis.
X-ray multigrain crystallography is a relatively new approach [1] and complementary to traditional crystallographic analysis which is based on either single crystals or powders. The experimental set-up is in the simplest case identical to that typically used in single crystal X-ray crystallography, with a monochromatic beam, a fully illuminated sample in transmission geometry on a rotary table and a 2D detector. The images acquired during a rotation of the sample may comprise up to a million diffraction spots from the grains simultaneously illuminated. A key step in the analysis of such data is multigrain indexing, i.e. associating diffraction spots with their crystal of origin.
Traditionally multigrain indexing requires a priori knowledge of the sample material and structure. At least the space group and the unit cells of the grains need to be known a priori in prior art indexing methods. The unit cell corresponds to the physical crystal lattice of a particular unknown grain and is defined by three lattice vectors. Hence, a brute force search and optimization procedure in the 9D space, spanned by these three lattice vectors, will provide an indexing of all grains. However, to our knowledge, such an approach is computationally not feasible.
Thus, it remains a problem to provide a more computational efficient method for indexing grains.